Health Data Science (Live Online)

Dec 7–16, 2021 $4,950 (Live Online)
May 3–12, 2022 $4,950 (Live Online)
Questions? Contact Us:
Stan Kachnowski
Director, Digital Health Program Series
Visiting Professor, IIT New Delhi
[email protected]
Format: Six days over two weeks with live sessions from 11 a.m. to 2 p.m. ET on Tuesdays, Wednesdays, and Thursdays.
View the live online schedule.
Certificate Credits: 3
Learn more.

In partnership with

Preferred pricing is available for groups of two or more. To inquire, email [email protected].

“We are at an inflection point in healthcare, with more data points accumulating in the industry than ever before. In addition, the COVID-19 pandemic has accelerated the virtualization of the healthcare system, bringing about a much-needed revolution in remote patient devices as well as the capturing, storing, analyzing, and visualizing of data. This has led to a transformation for machine learning, more commonly coined as artificial intelligence, resulting in the rapid growth of health data sciences. This program will provide a treatment for the definition, delineations, and details of technologies as well as techniques for executives to facilitate the incorporation of health data science into their organization.”
– Stan Kachnowski, Director of the Digital Health Program Series

Health Data Science

The program's faculty director Assaf Zeevi

Today, individual and population health can be significantly transformed by using digital tools. Health data science is an emerging discipline within the field, arising at the intersection of statistics, computer science, and health. It can generate data-driven solutions through better comprehension of complex real-world health problems, employing critical thinking and analytics to derive knowledge from big data.

Delving into the world of algorithms and analytics, this program explores the various technologies and techniques that are used every day around the world in amplifying the ability of healthcare data to provide value to large enterprises in a variety of sectors. The learning objectives will be driven by the needs of executives around how to apply data science in healthcare and life sciences today.

Please Contact Us

To learn more about this program, please contact Co-Director Stan Kachnowski at [email protected].


Data science in healthcare can save lives by predicting the probability that patients will suffer from certain diseases, providing AI-powered medical advice in rural and remote areas in underserved communities, customizing therapies for different patient profiles, or assisting in finding cures to cancer, AIDS, Ebola, and other terminal diseases.

Key learning outcomes from the program are:

  • Understand the terms, techniques, and technologies driving data science in healthcare and life sciences today
  • Learn about the landscape of artificial intelligence in healthcare innovation in times of COVID-19
  • Explore the major tasks for which machine learning is used and compare and contrast approaches for machine learning in healthcare
  • Learn about key concepts in predictive analytics and machine learning and its applications
  • Understand how the use of predictive analytics in healthcare can boost performance on a range of measures while also maximizing resources
  • See how data availability, improving computational power, and designing of digital- and data-centric organizations have fostered more effective data-driven business decisions
  • Develop your knowledge of various statistical tools and its applications to build skills for statistical inference of business data
  • Explore case studies on how data collected during routine patient care can inform precision medicine efforts for the population at large

Upon completion of this program, you will earn three credits towards a Certificate with select alumni and tuition benefits. Learn more.


The program currently takes place in a live online format and uses a combination of online tools, interactive lectures, case studies, and online workshops for individuals and groups.

You'll learn in a high-touch, intimate setting from a range of academic and industry experts. Sessions are taught by Columbia Business School professors, digital health practitioners, and business leaders, supplemented by sessions with colleagues from various fields and industries.

Sessions include:*

  • Introduction to Health Data Science
  • Artificial Intelligence in Healthcare
  • Predictive Analytics and Machine Learning
  • Leveraging Predictive Analytics
  • Digital Strategies for Operational Excellence
  • Case Studies in Precision Medicine
  • Managerial Statistics
  • Business Analytics and Data Science
  • Applying Data Science Tools and Techniques to Optimize Managed Care Performance
  • The Importance of Data Visualization as the Last Mile of the Health Data Science Marathon
  • Real-World Evidence for Innovative Solutions
  • Verily Panel: Strides in Digital Health during a Pandemic
  • Pharma's Role in Value-Based Healthcare
  • Applications of Data Science in Health Plans

*Sessions are subject to change.

For a complete program schedule download the agenda.


Health Data Science is designed for executives working in the rapidly evolving fields of life science innovation, pharmaceutical and device research, health tech investment, and other related industries. This program empowers participants to understand the complex digital health landscape and to both identify and capture meaningful opportunities to generate new value for both their organizations and customers.

Columbia Business School alumni and up to four of their colleagues are eligible for a 25 percent tuition benefit for this program. More on the Alumni Tuition Benefit.


Assaf Zeevi
Kravis Professor of Business
Columbia Business School

Assaf Zeevi is the Kravis Professor of Business at Columbia Business School. His research and teaching interests lie at the intersection of operations research, statistics, and machine learning. He has received several teaching and research awards including the CAREER Award from the National Science Foundation, the IBM Faculty Award, and the Google Research Award. He also serves on various editorial boards and program committees in the operations research and machine learning communities, as well as scientific advisory boards for startup companies in the high technology sector.

Stan Kachnowski

Stan Kachnowski is the Chair of the digital health organization HITLAB. He is an Oxford-trained researcher who has taught over 5,000 students from Columbia University, IIT-Delhi, and Quinnipiac College. His teaching and research over the past 25 years include educating graduate-level and executive students on four continents and conducting extensive studies on the efficacy and diffusion of digital health, including electronic data capture, ePRO, wearables, and predictive algorithms.

Along with the above, additional Columbia Business School faculty and industry experts contribute to and teach in the program.


Do you have questions about our live online programs? Please review our commonly asked questions on our live online programs FAQs page.